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Current issue

ELEKTRO 12/2017 was released on December 6th 2017. Its digital version will be available on January 5th 2018.

Topic: Measurement, measuring devices and engineering; Testing and diagnostics

Main Article
Measurements on rotating machines using SFRA method
Application possibilities of ultra-capacitors or LiFePO4 batteries in trolley network of the Brno Public Transit Company

SVĚTLO (Light) 6/2017 was released on December 11th 2017. Its digital version will be available on january 11th 2018.

Lighting installations
The lighting of university building Centrale Supélec in Saclay in France
The light for our future

Daylight
Application and judgment light guides Solatube®

Getting More Miles From Plug-in Hybrids

17.02.2016 | University of California | ucrtoday.ucr.edu

Plug-in hybrid electric vehicles (PHEVs) can reduce fuel consumption and greenhouse gas emissions compared to their gas-only counterparts. Researchers at the University of California, Riverside’s Bourns College of Engineering have taken the technology one step further, demonstrating how to improve the efficiency of current PHEVs by almost 12 percent.

Since plug-in hybrids combine gas or diesel engines with electric motors and large rechargeable batteries, a key component is an energy management system (EMS) that controls when they switch from ‘all-electric’ mode, during which stored energy from their batteries is used, to ‘hybrid’ mode, which utilizes both fuel and electricity. As new EMS devices are developed, an important consideration is combining the power streams from both sources in the most energy-efficient way.

Better efficiency of hybrid systems

While the UCR EMS does require trip-related information, it also gathers data in real time using onboard sensors and communications devices, rather than demanding it upfront. It is one of the first systems based on a machine learning technique called reinforcement learning (RL).

In comparison-based tests on a 20-mile commute in Southern California, the UCR EMS outperformed currently available binary mode systems, with average fuel savings of 11.9 percent. Even better, the system gets smarter the more it’s used and is not model- or driver-specific, meaning it can be applied to any PHEV driven by any individual.

Read more at University of California

Image Credit: Wikipedia

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